Python programmer állások X. kerületben (ai és automatizáció)

• Participation in security penetration testing projects
• Application-level penetration testing (e.g., web application, Android, or iOS Mobile application)
• Infrastructure level security penetration testing
• Red Teaming
• Automotive (car hacking)/Hardware/SCADA/IoT penetration testing

• Unterstützung des Teams bei der Automatisierung und dem Testen von Cisco SD-WAN basierten Netzwerktechnologien
• Entwicklung und Pflege automatisierter Testfälle mit Python und Robot Framework
• Nutzung von Jira für Aufgabenverfolgung
• Kommunikation über MS Teams

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, kubernets, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks before they become threats

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Experience in different Data Science topics including machine learning, LLM, deep learning
• Independent delivery of Data Science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

Ownership of detection capabilities from idea to customer impact across the AI/ML detection portfolio including threat similarity search, URL reputation, image-based phishing and brand-spoofing detection, web threat classification, and content classification...

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• Development and enhancement of T Cloud Public platform in a customer-oriented manner
• Operation of the built cloud platform
• Solving complex problems in the daily operation of a hyper-scaler's cloud backend
• Building tools to reduce occurrence of errors and improve customer experience

• Management of end-to-end software release process including branch management, software version control, release note documentation, and communication with internal and external collaborators
• Driving release automation by enhancing CI/CD pipelines and defect logging and tracking for releases

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Designing OpenStack-based network services on the T Cloud Public platform
• Operating OpenStack-based network services on the T Cloud Public platform
• Further developing OpenStack-based network services on the T Cloud Public platform
• Planning automation initiatives using modern frameworks

• Building, configuring and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Designing and operating NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Technology architect with T Cloud Public hands-on experience
• Deep expertise in public cloud architecture
• Strong understanding of VPC networking
• Strong understanding of IAM & federation
• Strong understanding of cloud security architecture
• Strong understanding of Kubernetes & container platforms